Comparing Crowdsourced Near-Miss and Collision Cycling Data and Official Bike Safety Reporting

Abstract

Official sources of cyclist safety data suffer from underreporting and bias. Crowdsourced safety data have the potential to supplement official sources and to provide new data on near-miss incidents. BikeMaps.org is a global online mapping tool that allows cyclists to record the location and details of near misses and collisions they experience. However, little is known about how the characteristics of near-miss and collision events compare. Further, the question remains whether the characteristics of crowdsourced collision data are similar to those of collision data captured by official insurance reports. The objectives of this study were twofold: ( a) to assess similarities and differences in near misses and collisions reported to BikeMaps.org and ( b) to assess similarities and differences in collisions reported to BikeMaps.org and to an official insurance data set. Logistic regression was used first to model the odds of crowdsourced near-miss reports as opposed to collision reports and then to model the odds of crowdsourced as opposed to official insurance collision reports, as a function of incident circumstances. The results indicated higher odds of crowdsourced reports of near misses than of crowdsourced collision reports for commute trips, interactions with motor vehicles, and in locations without bicycle-specific facilities. In addition, relative to insurance reports, crowdsourced collision reports were associated with peak traffic hours, nonintersection locations, and locations where bicycle facilities were present. These analyses indicated that crowdsourced collision data have potential to fill in gaps in reports to official collision sources and that crowdsourced near-miss reporting may be influenced by perceptions of risk.

Crowdsourced bicycling crashes and near misses: trends in Canadian cities

“…The gender breakdown from BikeMaps.org data used in this current analysis is presented by city in Table 2. A study of reports on BikeMaps.org from Metro Vancouver found that gender and age were not associated with the reporting of collisions relative to near misses (Branion-Calles et al, 2017). It should be noted that while cities usually have official bicycling crash data, access and completeness varies greatly across Canadian jurisdictions.…”

“…Evaluation of reports shows that there are some consistent differences between conditions that lead to near miss reporting, relative to collision reports. Data show that a higher odds of near miss reports are associated with commute trips, incidents involving motor vehicles, and in locations without bicycle-specific facilities (Branion-Calles et al, 2017). It is also true that the exact nature of what is reported as a near miss will vary, especially depending on the experience of the bicyclists.…”

“…Near misses are increasingly used as a proxy for crashes, particularly when crash numbers are small (Dozza, 2020). While the relationship between near misses and crashes is complex, determining the ratio of their relative frequencies in certain contexts can provide additional validity for using near misses as a surrogate measure (Branion-Calles et al, 2017;Dozza, 2020;Guo et al, 2010).…”

WeatherNet: Recognising Weather and Visual Conditions from Street-Level Images Using Deep Residual Learning

“…In this study, we refer to visual conditions as the significant changes in the appearance of cities during dawn/dusk, day or night-time including the effect of glare on visibility, whereas weather conditions are the meteorological changes of the represent crucial factors for many urban studies including transport, behaviour, and safety-related research [5]. For example, walking, cycling, or driving in rainy weather is associated with a higher risk of experiencing an incident than in clear weather [5,6]. Fog, snow, and glare have also been found to increase risk [6,7].…”

“…For example, walking, cycling, or driving in rainy weather is associated with a higher risk of experiencing an incident than in clear weather [5,6]. Fog, snow, and glare have also been found to increase risk [6,7]. Importantly, it is not only the inherent risk that different weather and visual conditions pose to human life that is of interest to researchers.…”